Summary: Since June 2019, under the umbrella of the national health insurance system, Japan has started cancer genomic medicine (CGM) with comprehensive genomic profiling (CGP) tests. The Ministry of Health, Labour and Welfare (MHLW) of Japan constructed a network of CGM hospitals (a total of 233 institutes as of July 1, 2022) and established the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), the national datacenter for CGM. Clinical information and genomic data from the CGP tests are securely transferred to C-CAT, which then generates “C-CAT Findings” reports containing information of clinical annotation and matched clinical trials based on the CGP data. As of June 30, 2022, a total of 36,340 datapoints of clinical/genomic information are aggregated in C-CAT, and the number is expected to increase swiftly. The data are now open for sharing with not only the CGM hospitals but also other academic institutions and industries.

Resistance to immune-checkpoint blockade remains challenging in patients with non-small cell lung cancer (NSCLC). Tumor-infiltrating leukocyte (TIL) quantity, composition, and activation status profoundly influence responsiveness to cancer immunotherapy. This study examined the immune landscape in the NSCLC tumor microenvironment by analyzing TIL profiles of 281 fresh resected NSCLC tissues. Unsupervised clustering based on numbers and percentages of 30 TIL types classified adenocarcinoma (LUAD) and squamous cell carcinoma (LUSQ) into the cold-, myeloid cell-, and CD8+ T cell-dominant subtypes. These were significantly correlated with patient prognosis; the myeloid cell subtype had worse outcomes than the others. Integrated genomic and transcriptomic analyses, including RNA sequencing, whole-exome sequencing, T cell receptor repertoire, and metabolomics of tumor tissue, revealed that immune reaction-related signaling pathways were inactivated, while the glycolysis and K-ras signaling pathways activated in LUAD and LUSQ myeloid cell-subtypes. Cases with ALK and ROS1 fusion genes were enriched in the LUAD myeloid subtype, and the frequency of TERT copy number variations was higher in LUSQ myeloid subtype than in the others. These classifications of NSCLC based on TIL status may be useful for developing personalized immune therapies for NSCLC.

PURPOSE This single-center, prospective molecular profiling study characterizes genomic alterations and identifies therapeutic targets in advanced pediatric solid tumors. METHODS As part of the TOP-GEAR (Trial of Onco-Panel for Gene profiling to Estimate both Adverse events and Response by cancer treatment) project at the National Cancer Center (NCC), Japan, we enrolled pediatric patients with a refractory or recurrent disease during August 2016-December 2021 and performed genomic analysis of matched tumors and blood using originally developed cancer gene panels, NCC Oncopanel (ver. 4.0) and NCC Oncopanel Ped (ver. 1.0). RESULTS Of 142 patients (age, 1-28 years) enrolled, 128 (90%) were evaluable for genomic analysis; 76 (59%) patients harbored at least one reportable somatic or germline alteration. The tumor samples were collected during the initial diagnosis in 65 (51%) patients, after treatment initiation in 11 (9%) patients, and upon either disease progression or relapse in 52 (41%) patients. The leading altered gene was TP53, followed by MYCN, MYC, CDKN2A, and CDK4. The commonly affected molecular processes were transcription, cell-cycle regulation, epigenetic modifiers, and RAS/mitogen-activated protein kinase signaling. Twelve (9%) patients carried pathogenic germline variants in cancer-predisposing genes. Potentially actionable findings were identified in 40 (31%) patients; to date, 13 (10%) patients have received the recommended therapy on the basis of their genomic profiles. Although four patients had access to targeted therapy through clinical trials, the agents were used in nine patients in an off-label setting. CONCLUSION The implementation of genomic medicine has furthered our understanding of tumor biology and provided new therapeutic strategies. However, the paucity of proposed agents limits the full potential of actionability, emphasizing the significance of facilitating access to targeted cancer therapies.

<p>Patient outcomes in immune subtypes. <b>A</b> and <b>B,</b> Kaplan–Meier EFS curves for subtypes of LUAD (A) and LUSQ (B). <i>P</i> values were calculated by multivariate Cox regression. <b>C</b> and <b>D,</b> Relationships of cell density (left) with �45 (right) for each immune cell type infiltrated in tumors to patient prognosis in LUAD (C) and LUSQ (D). Z-scores from Cox proportional hazards analysis are plotted; in the plots, red dots indicate <i>P</i> ≤ 0.05. <b>E</b> and <b>F,</b> Differences in histopathologic findings for immune subtypes of LUAD (E) and LUS (F). The <i>P</i> values determined using Fisher exact test w are plotted; in the plots, red circles indicate <i>P</i> ≤ 0.05 and filled red circles indicate Holm-adjusted <i>P</i> ≤ 0.2. <b>G</b> and <b>H,</b> Frequencies of each classification in immune subtypes in LUAD (G) and LUSQ (H). Numbers of patients are indicated in the bar segments.</p>

<p>Activated and suppressed pathways identified by GSEA using the hallmark gene set in immune subtypes. <b>A</b> and <b>B,</b> Heat maps representing top scored pathways enriched in genes with expression increased and decreased in common in LUAD (A) and LUSQ (B). <b>C</b> and <b>D,</b> Top signatures of pathways with increased expression are shown in red; those for genes with decreased expression are shown in blue. Running enrichment scores for glycolysis, IFNα, IFNγ, K-<i>ras</i> signaling, and TGFβ signaling signatures as commonly activated pathways in immune subtypes of LUAD (C) and LUSQ (D).</p>